Maize Yield Losses from Stemborers in Kenya

  • Hugo De GrooteEmail author
Research Article


Maize is the major food crop in Kenya, where 2.3 million tonnes are produced annually to feed an estimated 28.6 million people (79 kg/person p.a.). Population growth in the country is high (2.9 % p.a.), resulting in increased pressure on arable land and, consequently, increased pest pressure on crops. Stemborers are one of the most important pests of maize. Previous research with artificial infestation established clear links between damage factors and yield losses. These results, however, cannot be extrapolated to estimate crop losses in farmers’ fields under natural infestation. Due to lack of field data, farmers’ (often subjective) estimates of losses under natural infestation and the incidence of infestation were used to estimate maize yield losses for each of Kenya’s major agroecological zones. The yield loss was estimated to be 12.9 %, amounting to 0.39 million tonnes of maize, with an estimated value of US$ 76 million. High-potential areas have relatively low crop loss levels (10–12 %), while the low-potential areas have higher losses (15–21 %). Taking into account the higher yield of the former areas (more than 2.5 t/ha), the loss per hectare is remarkably constant, between 315 and 374 kg/ha, except for the dry mid-altitude zones, where losses total approximately 175 kg/ha. The value of these losses is estimated at US$ 61–75/ha and US$ 34/ha, respectively. Such estimates are useful for setting research and extension priorities.

Key Words

stemborer crop loss maize Kenya 


Le maïs est la principale culture au Kenya, avec 2,3 million de tonnes produites annuellement pour nourrir une population estimée à 28,6 million (79 kg/personne et par an). La croissance de la population dans le pays est élevée (2,9 % par an), avec pour conséquence une pression croissante sur les terres arables, et une augmentation des problèmes dues aux ravageurs. Les foreurs sont un des ravageurs les plus importants du maïs. Des études antérieures, effectuées à partir d’infestations artificielles ont établi une relation étroite entre les pertes des récoltes et les dégâts lies aux foreurs. Toutefois, ces résultats ne peuvent pas être utilisés pour estimer les pertes dans.les champs des paysans sous infestation naturelle. Pour palier à l’absence des données de terrains, les estimations des pertes sous infestation naturelle (souvent subjectives) et l’incidence de 1’infestation telles que founis par les paysans, ont été utilisés pour estimer les pertes en recolte de maïs dans chaque zone agroecologique importante du Kenya. Les pertes moyennes ont été estimées à 12.9 %, équivalent à 0.39 million de tonnes de maïs d’une valeur approximative de 76 million de dollars. Les régions à haut potentiel ont généralement un taux de pertes plus faible (10–12 %) que les régions à faible potentiels (15–21 %). En valeur absolue, et du fait de rendements plus élevés dans les regions a haut potentiel, les pertes par ha sont relativement constante entre 315 et 374 kg/ha, excepté dans la zone sèche d’altitude moyenne où les pertes totales sont de 175 kg/ha. La valeur de ces pertes est estimée à respectivement 61–75 dollars par hectare et 34 $/ha. Ce genre d’estimations est utiles à la détermination des priorités de recherche et de la vulgarisation agricole.

Mots Clés

foreur perte de recolte maïs Kenya 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Ajala, S. O. and Saxena, K. N. (1994) Interrelationship among Chilo partellus (Swinhoe) damage parameters and their contribution to grain yield reduction in maize (Zea mays L.). Appl Enfomol. Zool. 29, 469–476.CrossRefGoogle Scholar
  2. Alghali, A. M. (1992) Effects of cultivar, time and amount of Chilo partellus Swinhoe (Lepidoptera: Pyralidae) infestation on sorghum yield components in Kenya. Maydica 37, 371–376.Google Scholar
  3. Aquino, P., Carrion E. and Calvo, R. (1999) Selected Maize Statistics. Part 3 of CIMMYT1997/98 World Maize Facts and Trends; Maize Production in Drought-stressed Environments: Technical Options and Research Resource Allocation. CIMMYT, Mexico, D.F.Google Scholar
  4. Cardwell, K. E., Schulthess, F., Ndemah, R. and Ngoko, Z. (1997) A systems approach to assess crop health and maize yield losses due to pests and diseases in Cameroon. Agric. Ecosyst. Environ. 65, 33–47.CrossRefGoogle Scholar
  5. Cochran, W. G. (1977) Sampling Techniques. John Wiley and Sons, New York. 428 pp.Google Scholar
  6. De Groote, H. (1996) Optimal survey design for rural data collection in developing countries. Q. J. Int. Agric. 35, 163–175.Google Scholar
  7. Gounou, S., Schulthess, F., Shanower, T., Hammond, W.N.O., Braima, H., Cudjoe, A.R. and Antwi, K. K., with, I. Olaleye (1994) Stem and ear borers of maize in Ghana. Plant Health Management Research Monograph No. 4. International Institute of Tropical Agriculture (UTA), Ibadan, Nigeria.Google Scholar
  8. Gebre-Amlak, A., Sigvald, R. and Petersson, J. (1989) The relationship between sowing date, infestation and damage by the maize stalk borer, Busseola fusca (Noctuidae), on maize in Awassa, Ethiopia. Trop. Pest Manage. 35, 143–145.CrossRefGoogle Scholar
  9. Hassan, R. M. (Ed.) (1998) Maize Technology Development and Transfer: A GIS Application for Research Planning in Kenya. CAB International, Wallingford, UK/CIMMVT/KARI. 230 pp.Google Scholar
  10. Kumar, H. and Saxena, K. N. (1994) Infestation and damage on three maize cultivars by the stalk-borer Citilo partellus (Swinhoe) in relation to their yield in western Kenya. Insect Sci. Applic. 15, 331–335.Google Scholar
  11. LeClerg, E. L. (1971) Field experiments for assessment of crop losses. In Crop Loss Assessment Methods. FAO Manual on the Evaluation and Prevention of Losses by Pests, Diseases and Weeds (Edited by L. Chiarappa). FAO, Rome.Google Scholar
  12. Mulaa, M. A. (1995) Evaluation of factors leading to rational pesticide use for the control of the maize stalk borer Busseola fusca in Trans Nzoia district, Kenya. PhD thesis, University of Wales, Cardiff.Google Scholar
  13. Pingali P.L. (ed.) (2001) C1MMYT1999-2000 World Maize Facts and Trends. Meeting World Maize Needs: Technological Opportunities and Priorities for the Public Sector. CIMMYT, Mexico, D.F. 60 pp.Google Scholar
  14. Seshu Reddy, K. V. and Sum, K. O. S. (1991) Determination of economic injury of the stemborer, Chilo partellus (Swinhoe) in maize, Zea mays L. Insect Sci. Applic. 12, 269–274.Google Scholar
  15. Seshu Reddy, K. V. and Sum, K. O. S. (1992) Yield-infestation relationship and determination of economic injury level of the stem-borer, Chilo partellus (Swinhoe) in three varieties of maize, Zea mays, L. Maydica 37, 371–376.Google Scholar
  16. Swaine, G. (1957) The maize and sorghum stalkborer Busseola fusca in peasant agriculture in Tanganyika territory. Bull. Entomol. Res. 48, 711–722.CrossRefGoogle Scholar
  17. Walker, P. T. (1991a) Empirical models for predicting yield loss caused by one type of insect: The stemborers, pp. 133–137. In Crop Loss Assessment and Pest Management (Edited by P. S. Teng). APS Press, The American Phytopathological Society, St Paul, Minnesota.Google Scholar
  18. Walker, P. T. (1991b) Measurement of insect pest populations and injury, pp. 19–29. In Crop Loss Assessment and Pest Management (Edited by P. S. Teng). APS Press, The American Phytopathological Society, St Paul, Minnesota.Google Scholar
  19. Walker, P. T. (1991c) Quantifying the relationship between insect populations, damage, yield and economic thresholds, pp. 114–125. In Crop Loss Assessment and Pest Management (Edited by P. S. Teng). APS Press, The American Phytopathological Society, St Paul, Minnesota.Google Scholar

Copyright information

© ICIPE 2002

Authors and Affiliations

  1. 1.International Maize and Wheat Improvement Center (CIMMYT)NairobiKenya

Personalised recommendations